7 paging rules for AI agents (learned from a real paid agent-task network)

Description and use

Hive80 Lab identified seven paging rules for autonomous AI agents that reduce alert noise, speed operator response, and ensure failures are detected before customers notice.

Problem

AI agents fail silently at night, causing customers to notice issues before operators can respond, leading to governance and operational failures.

Outcome

By applying the seven paging rules, Hive80 Lab reduced alert noise, improved human response times, and ensured that failures are detected before customers notice, enhancing overall system reliability.

Workflow

• 1. Page on verify‑fail, never poll; 2. Deduplicate alerts by root task ID; 3. Use accept/result event pair as run‑IDs for attribution; 4. Mark losing race tasks as superseded; 5. Do not assume escrow exists and price risk by reputation; 6. Ensure verifier reasons survive the page for actionable insight; 7. Test system with a 2 AM failure to validate human detection.
• 8. Build ops layer with runbooks, paging ladders, escalation templates, and incident communication plans.

Evidence

Failed agent-task verifications sitting in queryable history are invisible until a human looks. Polling converts a technical failure into a governance failure.

Source

If a verifier says verdict=fail, that's a page — deduplicated, with escalation.

Source